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WP/12/xx
Economic Growth and the Sophistication of Production
Rahul Anand, Saurabh Mishra, and Nikola Spatafora
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© 2012 International Monetary Fund WP/12/xx
IMF Working Paper
Research Department
Economic Growth and the Sophistication of Production
Prepared by Rahul Anand, Saurabh Mishra, and Nikola Spatafora
Authorized for distribution by Andrew Berg
January 2012
This Working Paper should not be reported as representing the views of the IMF.The views expressed herein are those of the authors and should not be attributed to the IMF, its Executive Board, or its management. Working Papers describe research in progress by the authors and are published to elicit comments and to further debate.
Abstract
A new dataset on export sophistication reveals that in many countries the importance of modern services, and the sophistication of manufactured and service exports, has increased over time. However, this trend was less pronounced in LICs. Further, sophisticated exports can be an important contributor to overall growth, particularly if the economy is liberalized, the exchange rate is not overvalued, and there are good information flows. Finally, an educated workforce, external liberalization, and good information flows are important prerequisites for developing sophisticated goods and services. An appropriate macroeconomic policy is particularly important for goods, skilled labor and good information flows for services.
JEL Classification Numbers: F43, O14, O47
Keywords: Economic Growth, Sophistication of Production, Service Exports, sub-Saharan Africa.
Authors’ E-Mail Address: [email protected]; [email protected]; [email protected]
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Contents Page
I. Introduction..........................................................................................................................4
II. Stylized Facts.......................................................................................................................6A. The Structure and Evolution of Exports: General Points.........................................8B. The Structure and Evolution of Resource Exports................................................11C. The Structure and Evolution of Manufactured Exports.........................................13D. The Structure and Evolution of Service Exports...................................................15E. Export Sophistication: A More Formal Measure...................................................19
III. Economic Growth and Export Sophistication....................................................................26
IV. Determinants of Export Sophistication..............................................................................30
V. Concluding Remarks..........................................................................................................32
VI. Appendix............................................................................................................................34A. Data Description....................................................................................................34B. Constructing the Measure of Export Sophistication..............................................35C. Outlier Regressions................................................................................................41
VII. References..........................................................................................................................45
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I. INTRODUCTION1
In recent years, a small but rapidly growing literature has emerged, arguing that a key component of economic development and the growth process is an increase in the sophistication of a country’s production, and in particular of its exports. Fundamentals are important, but do not uniquely determine what a country will produce and export. Further, what a country produces and exports matters for growth: “… not all goods are alike in terms of their consequences for economic performance. Specializing in some products will bring higher growth than specializing in others” (Hausmann and others, 2007, henceforth HHR; see also Lall and others, 2005). Some products may yield greater knowledge spillovers, have a greater potential for backward and forward linkages, or offer an easier pathway toward other products with such characteristics. Ultimately, some products are more “sophisticated,” in the sense that they are associated with higher productivity levels, and those countries that latch on to such products will perform better. Over time, the sophistication of a country’s production structure may evolve, through either an increase in the quality of previously produced goods, or a move into new, more sophisticated products.
This paper makes four key contributions to the debate. First, it systematically documents changes in export sophistication over the past 20 years in low-income countries (LICs) and middle-income countries (MICs). In particular, it describes differences in the performance of different geographical regions, as well as between natural-resource–rich and other economies.
Second, the paper explicitly analyzes to what extent an increasing sophistication of production and exports translates into overall economic growth. A related question concerns what factors and mechanisms ultimately determine the magnitude of this impact. That is, what determines whether sophisticated sectors act as an engine of growth for the broader economy, or instead turn into isolated enclaves?
Third, the paper examines what enable a country to increase the sophistication of its production. In this context, the paper examines the relative importance of institutional factors, structural reforms, and policy measures (such as exchange rate policy).
Fourth, and perhaps most novel, the analysis moves beyond the usual focus on goods, and also considers services. The existing literature focuses on the sophistication of goods and its role in supporting growth. Yet services are gradually becoming more productive, tradable, and unbundled. Their growing importance is reflected in success stories such as India’s software and business-process activities, Nigerian’s film industry, Kenya’s call centers, Singapore’s knowledge-processing offices in legal and business consulting, Sri Lanka’s accountancy services, Abu Dhabi’s HR processing services firms, as well as the growing internationalization
1 We thank Andrew Berg, Olivier Blanchard, Ejaz Ghani, Ricardo Hausmann, Bernard Hoekman, Homi Kharas, Susanna Lundstrom Gable, Montfort Mlachila, Israel Osorio-Rodarte, Abebe Selassie, and seminar participants at the IMF and World Bank for valuable comments on an earlier draft. Lisa Kolovich provided outstanding research assistance.
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of innovation, R&D, design and marketing. Broadly speaking, as countries transition from low- to high-value-added activities, their growth paths can take different forms: manufacturing-intensive development as in China, or service-export–led growth as in India. Reflecting this, the paper uses a new measure of the sophistication of services, in addition to the sophistication of manufacturing and of goods overall, to analyze the transformation of global production (Mishra et al, 2011).2
The analysis yields three broad sets of conclusions. First, starting with the stylized facts, rich and fast-growing economies differ considerably from LICs and from sub-Saharan Africa (SSA) in terms of the composition and evolution of their export basket. Whereas rich and fast-growing countries have moved from resource-based to manufactured exports, the exports of LICs, and of SSA in particular, remain characterized by a relatively high share of natural resources and a relatively low share of manufactures. Further, LICs’ export baskets are relatively static, that is, over time they have moved into relatively few new products. In particular, while many countries have witnessed an increase in the relative importance of modern services, and are benefiting from the ongoing globalization of services, the LICs and SSA have largely failed to share in these trends. Ultimately, the sophistication of exports of both manufactures and services has increased over time. However, this trend has been less pronounced in both SSA and natural-resource–rich countries.
Second, increasing sophistication of exports, of both goods and services, can be an important contributor to overall economic growth. Sophisticated sectors are particularly likely to act as an engine of growth for the broader economy, rather than turn into isolated enclaves, if the economy is liberalized, the exchange rate is not over-valued, and there are good information flows.
Third, an educated workforce, external liberalization, and good information flows are important prerequisites for developing sophisticated exports of goods and services. An appropriate macroeconomic policy plays a particularly important role in sustaining sophisticated goods exports. Highly skilled labor and good information flows are especially critical for sophisticated service exports.
The rest of the paper is organized as follows. Section II outlines some key stylized facts. Section III analyzes formally whether and how the sophistication of exports affects overall economic growth. In turn, Section IV analyzes what factors enhance, or hold back, increases in the sophistication of production. Section V concludes. The Appendix describes the data and their sources.
2 “Sophistication” has a multitude of interpretations, but it broadly aims to capture the productivity level associated with a country’s production structure. This paper adopts a measure of sophistication based on whether the products exported by any given country are those typically exported by high-income or low-income economies.
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II. STYLIZED FACTS
This section outlines some key stylized facts, most of which are insufficiently appreciated. First, we discuss some potential drivers of growth, emphasizing the importance of the service sector. Second, we analyze the changing structure of production, and the extent to which countries have moved over time into more sophisticated sectors characterized by higher value-added goods and services.
The existing literature focuses on manufacturing, but does this sector represent the only plausible route to development? The data presented below suggest that growth in the service sector is an increasingly important component of the overall development process. As a corollary, ignoring services may yield misleading policy conclusions. Hence, later sections will focus on the sophistication of exports of not just goods, but also services.
Over the past decade, services have grown significantly as a share of global GDP, and currently account for 70 percent of total output. Figure 1 illustrates the share of manufacturing and of services in total GDP for countries at different stages of development.
Figure 1. Share of Manufacturing and Services in GDP versus Stage of Development, 2008
010
2030
4020
08 M
anuf
actu
ring
valu
e ad
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(Per
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of G
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4 6 8 102008 Ln(Per Capita GDP)
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4 6 8 102008 Ln(Per Capita GDP)
SSA East AsiaLA-Carib BRIC
Related to this, output growth is increasingly accounted for by industry and, in particular, services. Figure 2, panel A, illustrates sectoral contributions to overall GDP growth in developing countries for the periods 1995–99 and 2000–08. The contribution of services to growth in developing countries has increased significantly in the post–2000 period (Figure 2, panel B). In most developing countries, services are now the largest contributor to growth, accounting for 55 percent of the total.3
3 Related to this, Triplett and Bosworth (2004) find that services accounted for over 70 percent of the post–1995 surge in labor productivity in the United States.
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Figure 2. Panel A. Both Industry and Services Increasingly Contribute to Growth(Growth Accounting by Sectors, 1995–09 and 2000–08)
Panel B. Change in Growth Decomposition (2000–08 versus 1995–99)
Source: World Development Indicators, 2011.
Next, we tackle one key question: are countries moving over time into higher-tech, higher–value-added goods and services? To this end, we analyze the structure of production in some detail, looking at the composition of exports of goods, of manufactures, and of services. We examine
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the relative importance of various components, as well as the changes over time. In particular, we explore how the export baskets of rich and fast-growing countries differ from those of LICs and SSA, in terms of their current structure as well as their evolution.
In addition, we examine the evolution of resource and manufacturing exports from a slightly different viewpoint, analyzing whether countries are exporting more of the same products, or engaging in completely new economic activities. To this end, exports are classified into four categories: “Classical”, “Marginal”, “Disappearing”, and “Emerging” products. A “classical” product is defined as a product in which a country had a Revealed Comparative Advantage (RCA) in both the 1990–94 and 2005–09 sub-periods.4 In other words, the share of the product in the country’s total goods exports exceeded the share of the product in global cross-border exports both at the start and at the end of the sample period. “Marginal” products are instead those in which the country never had an RCA. “Disappearing” products are those in which a country had an RCA at the start, but not at the end, of the sample period. Conversely, “emerging” products are those in which a country only developed an RCA at the end of the sample period. Table 1 summarizes these definitions.
Table 1. Definition of “Classical”, “Marginal”, “Disappearing”, and “Emerging” Products.
A. The Structure and Evolution of Exports: General Points
To set the stage, we note that, over the past 20 years, total exports (relative to GDP) have increased in all major developing-country groups. In SSA, however, the increase was relatively small (Figure 3). Figure 4 illustrates the share of goods and of services in total exports, in 1990 and in 2009, for various regions.5
Figure 3. Export Share in GDP.
4 Formally, the RCA index for country C and product J is defined as: WTWJCTCJ EEEERCA /// , where E denotes exports, T denotes all products, and W denotes the world. The classification is based on COMTRADE trade data at the SITC 5-digit level.
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Source: World Development Indicators, World Bank. 2011.
5 Recorded cross-border service exports in 2007 amounted to $3.3 trillion, or 20 percent of total world trade. However, the share of services in trade rises to almost 50 percent if transactions are measured in value-added rather than in gross terms (Escaith, 2008). The value of trade in services rises further when adding in the sale of services by foreign affiliates of multinational firms. For instance, data for fifteen OECD countries puts the value of such sales at about $1.5 trillion in 2007 (WTO, 2009; Francois and Hoekman, 2010).
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Figure 4. Share of Goods and Service Exports in Total Exports, 1990 and 2009
Source: IMF Balance of Payments, 2011.
Next, we decompose export of goods into resource and primary products versus manufactures, and examine how this composition has changed over time. Figure 5 illustrates the structure of goods exports in different regions during the periods 1980–85 and 2007–09. Regions vary considerably, in terms of both the composition of their export basket, and changes over time in the relative importance of manufactures. The share of manufactured exports has increased considerably over time in High-Income Countries (HICs) and MICs; by the end of the period, manufactures accounted for almost 90 percent of China’s goods exports. On the other hand, resource-based products account for 90 percent of SSA’s exports of goods. Put differently, SSA’s manufactures, which in the early 1980’s accounted for a tiny 7 percent of total goods exports, by 2009 had expanded, but only to 13 percent of the total. In other LICs, the share of manufactures in total exports of goods actually decreased over time, to just over 20 percent. Thus, whereas HICs’ exports of goods are dominated by manufactures, the export baskets of LICs and SSA are still dominated by primary and resource-based products.
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Figure 5. Share of Resources and of Manufactures in Total Exports of Goods
Source: Authors’ calculations using COMTRADE SITC Rev. 3.
Next, we further decompose resource and manufactured exports into sub-categories to obtain a finer-grained picture of different regions’ export baskets.
B. The Structure and Evolution of Resource Exports
Figure 6 decomposes exports of resources into relatively simple primary products versus relatively higher-value-added resource-based products.6 The export baskets of HICs and fast-growing economies differ markedly from those of LICs and SSA. In particular, the share of primary products has remained constant or declined in most regions, with a particularly sharp decrease in fast-growing economies such as India or China. In contrast, SSA resource exports are dominated by primary products, whose share has remained constant over time. In other LICs, the share of primary products has actually increased sharply.
6 Examples of primary products include fresh fruit, rice, cocoa, tea, coffee, wood, coal, crude petroleum, and gas. Resource-based produced involve more processing, and can be based on either (i) agriculture or forestry (e.g., prepared meats and fruits, beverages, wood products, vegetable oil), or (ii) other resources (e.g., ore concentrates, petroleum and rubber products, cement, cut gems, glass). Resource-based products tend to be simple and labor-intensive (for instance, most food or leather processing), but some segments use relatively capital-, scale- and skill-intensive technologies (say, petroleum refining or modern processed foods).
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Figure 6. Resource Exports: Primary versus Resource-Based Products, 1980–85 and 2007–09
Source: Authors’ calculations using COMTRADE SITC Rev. 3.
Next, we plot classical, marginal, disappearing and emerging natural resources as a share of total resource exports (Figure 7). For both LICs and SSA, resource exports are dominated by classical products, with very few emerging new products. As of 2009, emerging natural resources, those that the country previously lacked a specialization in, accounted for 11 percent of SSA’s total.
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Figure 7. Share of Classical, Marginal, Disappearing, and Emerging Natural Resources in Total Resource Exports, Between 1990–94 and 2005–09.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sub-Saharan Africa
High Income Middle Income Other Low Income
Asia (excl. China and India)
India China
Emerging Marginal Disappearing Classical
Source: Authors’ calculations using COMTRADE data.
Overall, a decomposition of resource exports suggest that in this category LICs’ export baskets are still dominated by primary products and traditional export items. On the other hand, fast growing economies, such as India and China, have made a gradual shift towards resource-based and new types of resource exports.
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C. The Structure and Evolution of Manufactured Exports
Next, we divide manufactured exports into low-tech, medium-tech, and high-tech (Figure 8).7 The share of high-tech manufactures has broadly increased in HICs, in MICs, and in LICs, with a particularly large increase in China; however, it has actually declined in SSA. Medium-tech manufactures have grown across the board, but starting from a much smaller base in SSA and LICs.
7 Low-technology manufactures tend to have stable, well-diffused technologies, which are primarily embodied in capital equipment. Some of these products lie in the textile/fashion cluster (e.g., textile fabrics, clothing, headgear, footwear, leather manufactures, and travel goods). Other examples include pottery, simple metal parts and structures, furniture, jewelry, toys, and plastic products.
Medium-technology products comprise the bulk of skill- and scale-intensive capital goods and intermediate products. They form the core of industrial activity in mature economies. They tend to have complex technologies, with moderately high levels of R&D, advanced skill needs and lengthy learning periods. Examples include: (i) automotive products (passenger vehicles and parts, commercial vehicles, motorcycles and parts); (ii) process industries (synthetic fibers, chemicals and paints, fertilizers, plastics, iron, pipes/tubes); (iii) engineering industries (engines, motors, industrial machinery, pumps, switchgear, ships, watches).
High-technology products have advanced and fast-changing technologies, with high R&D investments and prime emphasis on product design. The most advanced technologies require sophisticated technological infrastructures, high levels of specialized technical skills, and close interactions both among firms, and between firms and universities or research institutions. Examples include: (i) electronics and electrical products (office/data processing/telecommunications equipment, TVs, transistors, turbines, power-generating equipment); (ii) other high tech (pharmaceuticals, aerospace, optical/measuring instruments, cameras); (iii) other transactions (electricity, cinema film, printed matter, “special” transactions, gold, art, coins, pets). See Lall (2000) for details on technology classification, and Appendix for examples.
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Figure 8. Share of Low-, Medium-, and High-Tech Manufactured Exports in Total Manufactured Exports
Figure 9 shows the share of classical, marginal, disappearing, and emerging manufactures in total manufactured exports of goods. Emerging products accounted for 20 percent of SSA’s manufactured exports, as opposed to more than half of LICs’ manufactured exports.
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Figure 9. Share of Classical, Marginal, Disappearing, and Emerging Manufactures in Total Manufactured Exports, Between 1990–94 and 2005–09.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sub-Saharan Africa High Income Middle Income Other Low Income Asia (excl. China and India)
India China
Emerging Marginal Disappearing Classical
Source: Authors’ calculations using COMTRADE data.
D. The Structure and Evolution of Service Exports
Service exports by developing countries almost tripled between 1997 and 2007. Perhaps more important, service exports have changed qualitatively. They are no longer exclusively an input into trade in goods; rather, they have increasingly become a final export which is directly consumed.
In particular, the mid-1990’s saw two seemingly separate but related developments. First, the revolution in information and communication technology (ICT). Second, rapid growth in the global forces often referred to as the 3Ts (technology, transportability, and tradability), with the advent of the internet age. Both events had a profound impact on the nature, productivity, and tradability of services (Ghani and Kharas, 2010). They resulted in rapid growth of what can be called modern services, such as business-processing services, accounting, business consulting, education, remote access services, medical-record transcription, entertainment, production services, design, and marketing. These services, unlike traditional services, increasingly require little face-to-face interaction, can be stored and traded digitally, and are not subject to many of
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the trade barriers that physical exports must overcome. They are becoming similar to manufactures in that they benefit from technological advancement, and their costs depend on economies of scale, agglomeration, networks, and division of labor. Ultimately, modern services are characterized by higher, and faster-growing, productivity levels (see Appendix).8
The world as a whole, as well as most regions and countries, witnessed an increase in the relative share of modern services after the late 1990’s (Figures 10 and 11). However, some developing countries, as well as SSA as a whole, actually experienced a decline in the relative importance of modern services.
Figure 10. Growth in Modern and in Traditional Service Exports, World, 2000–09
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2000 2001 2002 2003 2004 2005 2006 2007 2008
Modern Traditional
Source: Authors’ calculations using Balance of Payments, IMF.
8 Formally, we define modern services as comprising: finance; computer & information; royalties and license fees; and other business services. Traditional services comprise: communications; insurance; transportation; travel; construction; and personal, cultural and recreational services. Throughout, we focus on commercial service exports, and exclude government services.
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Figure 11. Share of Modern and of Traditional Services in Total Service Exports: 1990 & 2009
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1990 2009 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009
Sub-Saharan Africa Brazil China India Ireland United States
Traditional Modern
Source: Authors’ calculations using IMF Balance of Payments.
Focusing on the past decade alone, modern services have been growing relatively fast in MICs and in the BRICs (Figure 12). The opposite, however, holds for LICs and, in particular, for SSA. In a similar vein, in most countries service exports account for a rising share of total service-sector value added (Figure 13). Put differently, most countries are taking advantage of the globalization of services. However, the trend is far less marked in SSA.
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Figure 12. Traditional and Modern Service Exports: Recent Growth Trends, 2000–07
0
5
10
15
20
25
30
35
40
SSA South Asia MICs Other LICs Brazil China India USA
Traditional Modern
Source: Authors’ calculations using IMF Balance of Payments.
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Figure 13. Services Are Becoming Increasingly Tradable(Service Exports / Service Value Added (percent))
0
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4
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8
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12
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1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
SSA Other LICs MICs China India
Source: Authors’ calculations using IMF Balance of Payments and World Bank World Development Indicators.
E. Export Sophistication: A More Formal Measure
One of the contributions of this paper is to develop a more formal, continuous measure of the sophistication of exports of goods, manufactures, and services (based on the measure developed in Hausmann, Hwang and Rodrik, 2007, for goods alone). This measure can be thought of as
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representing the “quality” of a country’s export basket. Details of how the measure is constructed are given in the Appendix. Intuitively, the measure captures whether any given country’s export basket consists primarily of products typically exported by high-income economies (and viewed as relatively sophisticated) or by low-income economies (and viewed as relatively less sophisticated).
We begin by showing the different measures of sophistication. Overall, sophistication of exports of goods, manufactures, and services has increased over time (Figure 14). Levels of export sophistication are in general relatively low in both SSA, and natural-resource–rich countries (defined as those countries where natural resources, including minerals, account for at least 40 percent of exports). The evolution of sophistication had distinct trends for high growth, rich economies versus slow growing and poor economies. There has been a steady rise in goods sophistication for Asia, China and India, where China has moved up the value chain. SSA as a region lags behind most other regions. A similar trend is confirmed for manufacturing sophistication where China, Asia and India have moved up but SSA lags behind. Confirming our stylized facts, a distinct shift occurred through the late nineties and in the last decade across Asia and other emerging economies, where the goods export basket moved away from resource based production in more medium and high tech manufacturing.
A rising trend seems to highlight the analysis when we turn our attention to service export sophistication. In particular the rate of change is faster post 2000. Recent evidence shows that the increasing service export sophistication can be decomposed to primarily TFP gains rather than rises in income. In particular, the case for India is depictive of the significance of the measures. The composition of the Indian service export basket was similar to other countries in earlier nineties and they start out at relatively similar levels. However, with the tech boom the share of computer information services grew from nil increasing to 51 percent of total export basket by 2009. As the major component of service exports moved away from traditional activities to modern activities like business services and computer services, service export sophistication grew substantially more for India even given its income level.
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Figure 14. Export Sophistication over Time, for Goods, for Manufactures, and for Services. Split by Major Regions, and by Resource-Rich vs. Non-Resource-Rich Countries.
8.5
8.75
9
9.25
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9.75
10Non-Resource Rich
SSA HIC MICAsia India China
Goo
ds E
xpor
t Sop
hist
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ion
8
8.25
8.5
8.75
9
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9.5
9.75
10Resource Rich
SSA HIC MIC Asia
Goo
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xpor
t Sop
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19901992
19941996
19982000
20022004
2006
9
9.25
9.5
9.75Non-Resource Rich
SSA HIC MIC
Man
ufac
turi
ng E
xpor
t Sop
hist
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8.75
9
9.25
9.5
9.75
10Resource Rich
SSA HIC MIC Asia
Man
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ng E
xpor
t Sop
hist
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ion
19901992
19941996
19982000
20022004
2006
8.5
8.75
9
9.25
9.5
9.75Non-Resource Rich
SSA HIC MIC
Serv
ices
Exp
ort S
ophi
stic
atio
n
19901992
19941996
19982000
20022004
2006
8.5
8.75
9
9.25
9.5
9.75Resource Rich
SSA HIC MIC Asia
Serv
ices
Exp
ort S
ophi
stic
atio
n
Source: Authors’ calculations.
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Next, we look at the world and its sophistication considering the size of the economy. Chart 1 shows service export sophistication spectrum marked between red to black. The darker the intensity of black, the more sophisticated the country’s service exports. One can note that the India, UK and the USA are fairly sophisticated service exporters, whereas China’s grey presents relatively less sophisticated service exports. Similarly from dark to red to a lighter share presents primary specialization in traditional activities. The size of country bubble indicates the population size of the economy to gauge the importance of the economy in a global context. Similarly, goods and manufacturing sophistication are visualized in Chart 2 and 3 respectively. We note that China has become a sophisticated exporter of manufacturing versus India. Korea, Japan, USA and Europe continue to be more sophisticated whereas other pockets of Africa, Latin America and South Asia are less manufacturing sophisticated than India.
Next we turn our attention to how to view the different sophistication measure of manufacturing and service in Chart 4. We plot the two together in 2007 and create four quadrants by the mean. The second quadrant is countries which are fairly sophisticated in both sectors. The countries in the other quadrants are more specialized and sophisticated in one sector viz a viz the other. In order to look at a more dynamic view of the data and sophistication over time, we create Chart 5. Here the different measures of sophistication are plotted against each other over the sample periods 1990, 1995, 2000 and 2007. The different countries are depicted by different colors. By following one quadrant of the snapshot, one can see the evolving nature of sophistication globally and the correlation across them. Finally Chart 6 shows the relation of different regions with different colors over time with key determinants.
Overall, this section concludes that HICs and fast-growing economies differ systematically from LICs and SSA in terms of their export composition, and of how this has evolved over time. In particular, the export baskets of HICs and fast growers are characterized by a large and rising share of high value-added products. In the rest of the paper, we examine the relationship between export sophistication and growth within a more formal and rigorous framework.
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Chart 1. World Map Sophistication of Service Exports (red – traditional activities, dark black – sophisticated exports, size of the bubble - economy size proxied by population)
About Tableau maps: www.tableausoftware.com/mapdata
Sheet 2
1,841 53,358
dynamic_sexpy
Avg. pop_bl138
200,000
400,000
600,000
800,000
936,845
Map based on Longitude (generated) and Latitude (generated). Color shows sum of dynamic_sexpy. Size shows average of pop_bl. Details are shown for country. Thedata is filtered on year and Exclusions (country,year). The year filter keeps 1990, 1995, 2000 and 2007. The Exclusions (country,year) filter specifies a set.
Chart 2. World Map Sophistication of Goods Exports (orange – traditional activities, dark blue – sophisticated exports, size of the bubble - economy size proxied by population)
About Tableau maps: www.tableausoftware.com/mapdata
Sheet 2
2,644 21,253
Avg. exp_goods
Avg. pop_bl138
200,000
400,000
600,000
800,000
936,845
Map based on Longitude (generated) and Latitude (generated). Color shows average of exp_goods. Size shows average of pop_bl. Details are shown for country. Thedata is filtered on year and Exclusions (country,year). The year filter keeps 1990, 1995, 2000 and 2007. The Exclusions (country,year) filter specifies a set.
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Chart 3. World Map Sophistication of Manufacturing Exports (red – traditional activities, dark blue – sophisticated exports, size of the bubble - economy size proxied by population)
About Tableau maps: www.tableausoftware.com/mapdata
Sheet 2
3,570 18,966
Avg. exp_mfg
Avg. pop_bl138
200,000
400,000
600,000
800,000
936,845
Map based on Longitude (generated) and Latitude (generated). Color shows average of exp_mfg. Size shows average of pop_bl. Details are shown for country. Thedata is filtered on year and Exclusions (country,year). The year filter keeps 1990, 1995, 2000 and 2007. The Exclusions (country,year) filter specifies a set.
Chart 4. Benchmarking sophistication of countries
0K 2K 4K 6K 8K 10K 12K 14K 16K 18K 20K 22K
manufacturing export sophistication 2007
0K
2K
4K
6K
8K
10K
12K
14K
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18K
service export sophistication 2007
ZMB
YEM
URY
TUR
THA
SGP
SAU
RWA
PRY
POL
PHL
PAK
NZL
NPL
NIC
MUS
MOZ MEX
KOR
KEN
ITAISL
IRLIND
IDN
HTI
HND
GHA
GBR
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CYP
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COG
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CHE
CANBRA
BLZ
BGD
BDI
Average
Average
PAK
Sheet 3
regionadvance
East Asia & Pacific
Europe & Central Asia
Latin America & Caribbean
Middle East & North Africa
South Asia
Sub-Saharan Africa
Avg. gdppc_ppp_co322
10,000
20,000
30,000
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54,134
Average of exp_mfg vs. average of dynamic_sexpy. Color shows details about region. Size shows average of gdppc_ppp_co. The marks are labeled by code. Detailsare shown for countryname. The data is filtered on year, which keeps 2007. The view is filtered on countryname, Exclusions (countryname,region) and Exclusions(code,countryname,region). The countryname filter excludes Vietnam. The Exclusions (countryname,region) filter specifies a set. The Exclusions (code,countryname,re-gion) filter specifies a set.
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Chart 5. Snapshot of Sophistication partial correlation over time (colors represent different
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Chart 6. Sophistication with key determinants (color represents region, size is the per capita
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Average of ln_gdppc_ppp, average of yr_sch_ter, average of trademarkapplicationstotal, average of informationflow and average of restrictions vs. average of exp_goods, averageof dynamic_sexpy and average of exp_mfg. Color shows details about region. Size shows average of gdppc_ppp_co. Details are shown for country. The data is filtered on dy-namic_sexpy, exp_mfg, exp_goods and year. The dynamic_sexpy filter ranges from 1959 to 18730.47. The exp_mfg filter ranges from 3053 to 22427.86. The exp_goods filterranges from 2542 to 23296.6. The year filter keeps 1990, 1995, 2000, 2005 and 2007. The view is filtered on average of ln_gdppc_ppp and Exclusions (country,region). The aver-age of ln_gdppc_ppp filter ranges from 5.940 to 10.707. The Exclusions (country,region) filter specifies a set.
III. ECONOMIC GROWTH AND EXPORT SOPHISTICATION
Do increases in export sophistication matter for overall economic growth? And what factors magnify or, conversely, dampen this impact? To explore these questions, this section applies dynamic panel data estimation techniques, using data for over 100 countries over 1990–2008. In order to abstract from high-frequency business-cycle phenomena, the analysis examines the determinants of the three-year average growth rate of output per capita. The focus is on the sophistication of two different export categories: (a) overall goods exports; and (b) service exports. These sophistication measures are considered separately, owing to strong collinearity among them.
The analysis also controls for various standard determinants of growth, including in particular the following institutional, structural, and policy factors:
Initial Income per Capita. This captures convergence effects. Human Capital. This is measured using total years of schooling.9
External Liberalization. This composite measure is based on the following factors, with the weight of each factor in parentheses: (i) hidden import barriers (22%); (ii) mean tariff
9 To check robustness, the analysis also employed the latest available data on educational attainment from Barro and Lee (2010). Again, the key results did not change.
28
rate (28%); (iii) taxes on international trade / current revenue (27%); and (iv) capital account restrictions (23%). The source is the KOF Globalization Index; see Appendix I for more details.
Financial Development. This is measured using (private sector credit / GDP). Country- and Time-Level Fixed Effects.
The formal regression specification is as follows:
y i ,t− y i , t−1=α yi ,t−1+β lnEXPY i , t−1+φ GDi , t−1+ϑ i+εi ,t (1)
where y i ,t is the natural logarithm of GDP per capita, y i ,t−1 is the level of GDP per capita at the beginning of each three-year period, EXPY i , t−1 is the measure of export sophistication, GD i ,t−1 are the other growth determinants, ϑ i are the country-level fixed effects, and ε i ,t is the error term. Throughout, export sophistication is normalized by multiplying by the relevant (goods or services) export ratio.
Overall, the results indicate that export sophistication is an important driver of growth in developing economies (Tables 2 and 3). Initial export sophistication, of both goods and services, is associated with subsequent output growth, even after controlling for financial development, human capital, and external liberalization. Statistically, the impact is significant. The magnitude of the effects is economically relevant. A one standard deviation increase in the sophistication of goods or of services is associated with a, respectively, 0.6 or 0.4 percentage points increase in the average annual growth rate.10 Put differently, if developing countries were to increase the sophistication of their goods or services to the levels observed in advanced economies, their per capita growth rate would increase by, respectively, 1.1 or 0.5 percentage points. The estimated economic magnitudes remain stable over time, and are larger in the sub-sample of developing countries alone.
Table 2. Panel Regressions. Dependent Variable: Growth in Income Per Capita (3-Year Average). Independent Variable: Sophistication of Goods Exports
(1) (2) (3) (4) (5) (6)Post 1998 Developing countries
Log initial GDP per capita -3.969*** -7.866*** -8.211*** -7.216*** -7.974*** -5.448***(0.92) (1.13) (1.15) (1.32) (1.58) (1.24)
Log initial Goods EXPY 0.65* 0.654* 0.663* 0.694* 0.843* 0.626*(0.36) (0.37) (0.38) (0.38) (0.44) (0.39)
Years of Schooling 3.798*** 2.611*** 2.533*** 3.835*** 2.799***(0.78) (0.87) (0.88) (1.08) (1.01)
External Liberalization 1.147*** 1.181*** 2.071*** 0.933**(0.30) (0.30) (0.39) (0.37)
10 Based on our preferred specifications, in Table 2, column 4, and Table 3, column 4.
29
Financial Development -0.508 -0.894** -0.32(0.36) (0.40) (0.42)
Constant 17.85** 34.57*** 29.90*** 24.19** 15.99 25.05**(7.920) (8.982) (9.128) (10.01) (11.69) (12.30)
Observations 630 527 486 483 398 308R-squared 0.039 0.114 0.150 0.155 0.249 0.151Number of countries 153 123 111 111 110 78
Notes: Regressions include country-level fixed effects. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in semi-standardized form (that is, the original coefficients are multiplied by the overall standard deviation of the independent variable). Robust standard errors are in parentheses.
Table 3. Panel Regressions. Dependent Variable: Growth in Income Per Capita (3-Year Average). Independent Variable: Sophistication of Service Exports
(1) (2) (3) (4) (5) (6)Post 1998 Developing countries
Log initial GDP per capita -5.63*** -7.664*** -7.752*** -7.497*** -7.249*** -5.759***(0.98) (1.16) (1.18) (1.34) (1.61) (1.25)
Log initial Service EXPY 0.721*** 0.46*** 0.447** 0.455** 0.322* 0.537**(0.14) (0.17) (0.18) (0.18) (0.19) (0.22)
Years of Schooling 2.904*** 1.889* 1.885* 3.075** 2.345**(0.87) (0.96) (0.97) (1.19) (1.13)
External Liberalization 1.014** 1.034*** 2.045*** 0.766**(0.30) (0.30) (0.40) (0.38)
Financial Development -0.116 -0.371 0.182(0.34) (0.38) (0.39)
Constant 16.38*** 30.92*** 25.53*** 23.75*** 14.62 21.62*(6.188) (7.350) (7.618) (8.401) (9.920) (11.29)
Observations 664 553 507 504 412 329R-squared 0.069 0.099 0.127 0.128 0.197 0.132Number of Countries 152 123 111 111 110 80
Notes: Regressions include country-level fixed effects. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in semi-standardized form (that is, the original coefficients are multiplied by the overall standard deviation of the independent variable). Robust standard errors are in parentheses.
An important question is whether increasing sophistication automatically translates into a broader economic take-off. A natural hypothesis is that the link between export sophistication and growth may be stronger in economies with a more appropriate macroeconomic policy, more liberalized markets, and better information flows. Such conditions will facilitate inter- and intra-sectoral resource reallocation, as well as knowledge and technology spillovers. In the absence of these conditions, a sophisticated export sector may remain an isolated enclave, rather than triggering economy-wide growth. To test this hypothesis, we construct measures of:
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Overall Macroeconomic Policy. This is proxied by an index of real exchange rate overvaluation, constructed following Johnson, Ostry, and Subramanian (2010). We test for and find asymmetric effects, and therefore adopt an asymmetric variant of the index, where the extent of real exchange rate overvaluation is censored below zero.
Information Flows. This composite measure is based on the following factors, with the weight of each factor in parentheses: (i) internet users per 1000 people (36%); (ii) televisions per 1000 people (37%); and (iii) trade in newspapers / GDP (28%). The source is the KOF Globalization Index. This measure aims to capture the likelihood of knowledge spillovers.
The evidence suggests that, indeed, sophistication of goods exports has a greater impact on growth when the economy is liberalized and macroeconomic policy is appropriate (Table 4). It should be emphasized that, given the asymmetric specification, overvaluation reduces the positive growth spillovers from a sophisticated export sector, but undervaluation yields no corresponding benefits. In a similar vein, sophistication of service exports has a greater impact when the economy is liberalized, and in the presence of good information flows (Table 5).
Table 4. Panel Regressions. Dependent Variable: Growth in Income Per Capita (3-Year Average). Independent Variable: Sophistication of Goods Exports.
(1) (2) (3) (4) (5)
Log initial GDP per capita -3.969*** -4.747*** -5.469*** -4.977*** -6.015***(0.91) (1.16) (1.11) (1.03) (1.07)
Log initial Goods EXPY 1.656* 1.857* 4.247*** 1.824 0.728(0.35) (0.38) (0.39) (0.45) (0.46)
Overvaluation 0.256 -0.09(0.41) (0.40)
Overvaluation * Goods EXPY -3.585***(0.55)
External Liberalization 0.912*** 0.239(0.32) (0.38)
External Liberalization * Goods EXPY 1.633***(0.46)
Constant 17.85** 17.47* 42.90*** 20.95** 34.41***(7.920) (9.220) (9.640) (9.866) (10.68)
Observations 630 559 559 530 530R-squared 0.039 0.042 0.130 0.060 0.082Number of Countries 153 137 137 123 123
Notes: Regressions include country-level fixed effects. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in semi-standardized form ( that is, the original coefficients are multiplied by the overall standard deviation of the independent variable). Robust standard errors are in parentheses.
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Table 5. Panel Regressions. Dependent Variable: Growth in Income Per Capita (3-Year Average). Independent Variable: Sophistication of Service Exports.
(1) (2) (3) (4)
Log initial GDP per capita -5.63*** -7.363*** -9.465*** -6.996***(0.98) (1.03) (1.06) (1.18)
Log initial Service EXPY 0.721*** 0.353** 0.026 0.524***(0.14) (0.16) (0.16) (0.18)
Information Flows 1.418*** 0.02(0.31) (0.38)
Information Flows * Service EXPY 2.232***(0.21)
External Liberalization 0.425(0.37)
External Liberalization * Service EXPY 0.994***(0.42)
Constant 16.38*** 38.32*** 63.72*** 26.71***(6.188) (7.740) (8.620) (7.750)
Observations 664 664 664 553R-squared 0.069 0.106 0.164 0.088Number of Countries 152 152 152 122
Notes: Regressions include country-level fixed effects. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in semi-standardized form (that is, the original coefficients are multiplied by the overall standard deviation of the independent variable). Robust standard errors are in parentheses.
Having established the importance of export sophistication, and uncovered some of the factors explaining its heterogeneous impact on growth, the paper now turns to the determinants of export sophistication.
IV. DETERMINANTS OF EXPORT SOPHISTICATION
This section considers separately the determinants of export sophistication in goods and in services. The choice of potential determinants is difficult, given the lack of literature on this topic. The analysis considers the impact of the following variables:
Human Capital. This is measured using total years of schooling, and years of schooling in tertiary education, when examining the determinants of, respectively, goods and services sophistication.11
External Liberalization; Overall Macroeconomic Policy; Information Flows. These are all defined as in the previous section.
11 Our prior was that skilled labor might be especially important for producing sophisticated services. Indeed, for sophistication of goods, the impact of tertiary education was not statistically significant. For sophistication of services, all measures of schooling were significant.
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Given some evidence of non-stationarity, we estimate the relationships using FMOLS for heterogeneous cointegrated panels. Overall, the results indicate that an educated workforce, external liberalization, and good information flows are all significantly associated with greater sophistication of exports of goods and services, across a broad range of different specifications (Tables 6 and 7). An appropriate macroeconomic policy plays a particularly important role in sustaining sophisticated goods exports. Again, given the asymmetric specification, overvaluation acts to reduce the sophistication of goods exports, but undervaluation yields no corresponding benefits. In addition, highly skilled labor and good information flows are especially critical for sophisticated service exports.
Table 6. Cointegrating Panel Regressions. Dependent Variable: Sophistication of Goods Exports. Independent Variables: Institutional / Structural / Policy Factors.
(1) (2) (3) (4) (5)
Log GDP per capita 0.97*** 0.47*** 0.60*** 0.73*** 0.87***(32.64) (17.47) (14.45) (15.36) (9.13)
Years of Schooling 0.34*** 0.34*** 0.17*** 0.10***(5.23) (5.83) (4.82) (5.64)
External Liberalization 0.29 0.03 0.06**(1.54) (0.96) (2.02)
Overvaluation -0.02 -0.09***(1.31) (4.02)
Information Flows 0.17**(2.02)
Observations 684 684 684 684 684Number of Countries 38 38 38 38 38
Notes: Regressions estimated using FMOLS for co-integrated heterogeneous panels. Both country- and time-effects are included. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in standardized form (that is, the original coefficients are multiplied by the overall standard deviation of the independent variable, and divided by the overall standard deviation of the dependent variable). Robust t-statistics are in parentheses.
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Table 7. Cointegrating Panel Regressions. Dependent Variable: Sophistication of Service Exports. Independent Variables: Institutional / Structural / Policy Factors.
(1) (2) (3) (4) (5)
Log GDP per capita 1.52*** 0.86*** 0.65*** 0.76*** 0.49***(72.40) (29.13) (22.41) (20.96) (14.46)
Years of Tertiary Schooling 0.40*** 0.40*** 0.32*** 0.34***(14.33) (15.15) (17.11) (19.68)
External Liberalization 0.02*** 0.02*** 0.02***(4.62) (4.45) (4.93)
Overvaluation 0.01*** 0.00***(3.10) (2.61)
Information Flows 0.50***(8.04)
Observations 684 684 684 684 684Number of Countries 38 38 38 38 38
Notes: Regressions estimated using FMOLS for co-integrated heterogeneous panels. Both country- and time-effects are included. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. All coefficients are presented in standardized form (that is, the original coefficients are multiplied by the overall standard deviation of the independent variable, and divided by the overall standard deviation of the dependent variable). Robust t-statistics are in parentheses.
The magnitude of the effects is economically relevant. A one standard deviation increase in human capital or in external liberalization is associated with a, respectively, 0.1 or 0.06 standard deviation increase in the sophistication of goods exports.12 Put differently, if developing economies raised total years of schooling or external liberalization to the level observed in advanced economies, the gap in the sophistication of goods exports between advanced and developing economies would shrink by, respectively, 15 percent and 8 percent.
Likewise, a one standard deviation increase in tertiary human capital or in information flows are associated with a, respectively, 0.34 or 0.5 standard deviation increase in the sophistication of services exports.13 Put differently, if developing economies raised tertiary schooling or information flows to the level observed in advanced economies, the gap in the sophistication of service exports between advanced and developing economies would shrink by, respectively, 42 and 53 percent.
V. CONCLUDING REMARKS
The analysis yields three broad sets of conclusions. First, starting with the stylized facts,
12 Based on our preferred specifications, in Table 6, column 5.13 Based on our preferred specifications, in Table 7, column 5.
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Over time, rich and fast-growing countries have moved away from resource-based to manufactured exports.
In contrast, the exports of LICs, and of SSA in particular, remain characterized by a relatively high share of natural resources, and a relatively low share of manufactures. Further, LICs’ export baskets are relatively static, that is, over time they have moved into relatively few new products. That said, SSA resource exports are slowly moving up the value chain.
Services are becoming an increasingly important contributor to output growth and export performance.
Many countries have witnessed an increase in the relative importance of modern services. Linked to this, they are benefiting from the ongoing globalization of services. However, the LICs and SSA have largely failed to share in these trends.
Ultimately, the sophistication of exports of both manufactures and services has increased over time. However, this trend has been less pronounced in both SSA and natural-resource–rich countries.
Second, increasing sophistication of exports, of both goods and services, can be an important contributor to overall economic growth. Sophisticated sectors are particularly likely to act as an engine of growth for the broader economy, rather than turn into isolated enclaves, if the economy is liberalized, the exchange rate is not over-valued, and there are good information flows. In more distorted economies, there may be less scope for inter-sectoral and intra-sectoral resource allocation, as well as knowledge and technology spillovers.
Third, an educated workforce, external liberalization, and good information flows are all significantly associated with greater sophistication of exports of goods and services, across a broad range of different specifications. An appropriate macroeconomic policy plays a particularly important role in sustaining sophisticated goods exports. Highly skilled labor and good information flows are especially critical for sophisticated service exports.
Future research should explore the robustness of these findings. In particular, it will be important to consider alternative measures of sophistication, based for instance on whether a good or service are typically consumed (rather than produced) in advanced economies.
One final consideration. Neither China’s manufacturing-led growth strategy, nor India’s IT-enabled service growth, should be seen as a universal model for growth and development. However, the recent transformation of services provides some important and encouraging lessons, and country-specific ways of adapting to this ongoing phenomenon could provide an alternative path to growth.
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VI. APPENDIX
A. Data Description
The trade data used to construct the export sophistication indices are drawn from the IMF Balance of Payments statistics. Because of incomplete and inconsistent data reporting, our sample covers approximately 100 countries during 1990–2007. GDP per capita data is taken from the World Bank Indicators database.
Appendix Table 1 describes the main categories of export services. Some other key variables used in the regressions are defined as follows:
External Liberalization and Hidden Import Barriers. Source: Gwartney et al. (2010). The index is based on the Global Competitiveness Report’s survey question: “In your country, tariff and non-tariff barriers significantly reduce the ability of imported goods to compete in the domestic market.” The question’s wording has varied slightly over the years.
Taxes on International Trade (percent of current revenue). Source: World Bank (2010). Taxes on international trade include import duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes. Current revenue includes all revenue from taxes and nonrepayable receipts (other than grants) from the sale of land, intangible assets, government stocks, or fixed capital assets, or from capital transfers from nongovernmental sources. It also includes fines, fees, recoveries, inheritance taxes, and nonrecurring levies on capital. Data are for central government and in percent of all current revenue.
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Appendix Table 1. Data Description: Breakdown of Export Services.
Export Service Category Explanation
Transportation Transportation covers all transportation (sea, air, land, internal waterway, space, pipeline, etc) services that are performed by residents of one economy for those of another and that involve the carriage of passengers, goods (freight), rentals of carriers with crew, and related supporting services.
Travel Travel differs from the other categories in the sense that the consumer (traveler) moves to the location of the provider (a resident of the economy) and what is covered by the travel category are those goods and services acquired during the visit (less than a year). The international carriage of the traveler is covered under transportation. The measure can be interpreted as a proxy for international tourism, business travelling and international student (even if staying longer than one year).
Communication Communication covers (i) telecommunication and (ii) postal and courier between residents and nonresidents international transactions.
Construction These are construction services performed by employees outside the country of the location of the enterprise. It also includes the goods the employees bring with them abroad to perform the task. Expenditures for local good though are recorded under Other business services.
Insurance Insurance services cover insurance provided by a resident to a nonresident and vice versa. It would often be freight insurances but also other direct services.
Financial Financial services cover financial intermediary and auxiliary services (except those of insurance enterprises and pension funds) between residents and nonresidents. This could be fees related to letters of credit, lines of credit, financial leasing, foreign exchange transaction, transaction in securities, asset management, etc, etc.
Computer Information Computer data and new-related service transactions between residents and nonresidents. These could be data bases, data processing, hardware consultancy, software implementation, maintenance and repair of computers, new agency services, etc.
Royalties & license fees These are exchange of payments between residents and nonresidents for the use of intangible and nonfinancial assets or property rights such as patents, copy rights, franchising, manuscripts, films, etc).
Other business Other businesses include (i) Merchanting (the purchase of goods by a resident from a nonresident and the subsequent resale to another nonresident, during which the good does not leave the compiling country), (ii) Operational leasing without operators covers resident-nonresident leasing, and charter without crew, (iii) Miscellaneous services, including (a) legal, accounting, management consulting, public relation services, (b) advertising and market research services, (c) research and development services, (d) architectural, engineering and other technical services, (d) agricultural, mining and on-site processing services, and (e) other services between residents and nonresidents.
Personal & cultural These services are divided into (i) audiovisual (services and fees for motion pictures—including to actors and producers, radio and television programs and musical recordings) and (ii) other (services related to museums, libraries, sporting, correspondence courses, etc).
B. Constructing the Measure of Export Sophistication
To formalize the notion of sophistication, a measure of export sophistication (EXPY) is constructed using the framework developed in Hausmann, Hwang and Rodrik (2007). This index
37
aims to capture the productivity level associated with a country’s export and is a proxy for the most productive set of products the country can produce at a given time. The choice of exports as proxy is guided by the idea that they reveal the production frontier as countries can be expected to export those products in which they are most productive, as well as, the availability of data.
EXPY’s are computed for three categories of exports: goods, manufactured goods, and services. In order to calculate the EXPY’s, each category of goods, manufactured and service exports is ranked according to the income levels of the countries that export it.14 Products exported by rich countries (controlling for overall economic size) are ranked higher than products exported by poor countries. These product-specific calculations are then aggregated to construct the country-wide indices of export sophistication.
Specifically, let countries be indexed by j and products be indexed by l. Let p be an export category (that is, goods, manufacturing, or services). Total exports of category p from country j equal
l
ppj jl
xX
Let Yj denote the per-capita GDP of country j. Then the productivity level associated with product k in category p, PRODY k
p, equals the weighted average of per capita GDPs, where the weights represent the revealed comparative advantage of each country in that product:
jj j
pj
pjk
pj
pjkp
k YXx
XxPRODY
)/(
)/(
The numerator of the weight, pj
pjk Xx , is the value-share of the product in the country’s
category p export basket. The denominator of the weight, j
pj
pjk Xx
, aggregates the value-shares across all countries exporting that product in that category.
Next, the PRODY’s are used to compute the productivity level associated with country j’s export basket of goods, manufactured goods, or services, EXPY J
P(export sophistication). Specifically, EXPY J
P is the average income and productivity level associated with all products in a given category exported by a country. It is computed as the weighted average of all relevant PRODY’s, where the weights represent the share of the relevant product in the country’s export basket. Thus,
pi
lp
i
pilp
i PRODYXx
EXPY
14 Our focus is on commercial service exports. Government services are therefore excluded when measuring Service EXPY.
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EXPYs are constructed for each country and for each year with available data. The Goods and Manufacturing EXPY’s are constructed using static PRODY’s, that is, the PRODY for each good is held constant at the average value during 2005–09. This means that any increase in EXPY measures a country’s jump from a low PRODY product to a high PRODY product, that is, the share of high PRODY goods in the export basket increased.
In contrast, the Service EXPY is constructed using dynamic PRODY’s, that is, the PRODY for each service is updated every year. Hence, an increase in the dynamic Service EXPY may reflect: (i) an increase in the PRODY of a service; and/or (ii) an increase in the share of high PRODY products in the export basket. This is important for two reasons. First, it allows us to capture the effect of changes in PRODY on EXPY. We want to measure not only the fact that countries are increasingly engaging in higher-value service exports, but also that the service exports themselves are increasing in sophistication.15 Second, service exports are not measured in as much detail as goods exports: we only have ten broad categories of service exports. This limits the extent to which we can understand the mechanisms at play. In particular, if a country moves, within the same service export category, from a sub-category of services with low PRODY to a sub-category with high PRODY, this will not show up at all in the static EXPY. However, it will show up in the dynamic EXPY, since this allows the PRODYs to change over time.
At this stage, we acknowledge some limitations in the interpretation of Service EXPY, owing to the way the data are recorded. First, the limited disaggregation mentioned above is sometimes exacerbated by the further aggregation in what the countries report. Second, even though there may have been no productivity improvements in a particular service that a country exports, it may still register an increased PRODY for that export if the broader category it belongs to made productivity improvements.16
Turning to the actual data, in general, higher-value-added goods and services have higher recorded PRODY (Appendix Table 2).
15 One potential issue with dynamic PRODY’s is that as developing countries start producing high PRODY services, the PRODY’s themselves decrease, owing to developing countries’ lower income levels. However, at this point, developing countries’ share of exports of high PRODY services is still too small to have an overall impact. A high PRODY service in the export basket of a small country may have a large impact on that country’s Service EXPY, but it will not affect that service’s overall PRODY.16 For instance, India did not export any computer & information services (CIS) from 1990 until later in the 1990’s. With the ICT boom, the CIS share in India’s service exports rose to 0.43. With the PRODY for CIS rising fast, India’s Service EXPY matched that of the UK by 2007, even though its income per capita was substantially lower. Again, Saudi Arabia has recorded all its services exports from 1990 through 2007 under the category “other business services” (OBS). The PRODY for OBS, which includes management consulting, legal services, accounting, auditing and other professional and miscellaneous services, is relatively high. As it increased over time, Saudi Arabia’s Service EXPY also rose, and by 2007 it was on a par with the United States’.
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Appendix Table 2. PRODY for Various Categories of Goods and Services
GOODS SERVICES
Primary Products
Resource Based
Low Tech
Medium Tech
High Tech Transport Construction
Royalty and
License Fees
Computer and
InformationFinancial
Average PRODY 10,425 14,827 13,63
5 19,070 21,814 10,189 11,828 12,912 17,791 22,763
The evolution over time of the PRODYs for each service category is presented in Appendix Tables 4 and 5. The columns on the left (transportation, travel, communication and construction) represent traditional services, while the columns on the right (insurance, financial, computer & information, royalties & license fees, other business services, and personal, cultural & recreational services) represent modern services. In general, the PRODY of modern services are higher and have been growing more rapidly.
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Appendix Table 3. Sophistication of Service Exports, by Category, at Global Level
Year Transportation Travel Communication Construction Insurance Financial Computer & Information
Royalties & License Fees
Other Business Services
Personal, Cultural & Recreational
Services
1990 7,420 7,372 7,343 13,073 6,906 20,649 16,414 10,040 7,456 18,0541991 7,936 7,489 7,307 16,415 6,956 17,560 16,073 7,424 7,342 16,3031992 7,981 7,193 6,801 17,275 7,817 19,216 14,403 8,656 7,648 12,0581993 8,164 7,311 4,934 14,453 7,823 17,603 14,644 8,999 7,856 6,3941994 8,255 7,542 5,241 13,066 8,278 14,871 11,120 9,407 8,299 8,6951995 9,214 7,691 5,937 12,780 11,222 21,643 16,844 17,054 8,698 11,6071996 9,135 7,828 6,255 12,840 11,448 22,384 17,131 15,034 8,920 12,7831997 9,263 7,943 6,174 8,980 11,498 23,841 18,015 11,576 9,107 13,9531998 9,800 7,684 6,346 10,104 11,201 22,416 22,789 12,153 9,710 12,3441999 10,319 7,951 6,503 10,210 11,075 23,612 22,433 14,409 10,013 13,2162000 10,516 8,082 6,553 10,422 10,856 24,409 19,852 14,973 10,763 14,2822001 11,213 8,408 6,552 9,695 10,496 25,160 18,058 15,318 11,132 14,6132002 11,559 8,696 6,467 9,185 13,842 24,862 17,906 14,828 11,812 13,4422003 11,870 8,769 6,926 8,232 15,187 22,486 17,961 14,670 12,725 13,6152004 12,656 9,086 7,932 9,494 14,894 23,871 19,150 12,611 13,175 14,4912005 12,575 9,312 9,205 11,402 15,725 25,444 19,226 14,610 13,940 15,3742006 12,779 9,653 9,522 12,691 14,316 28,546 19,090 12,488 15,557 16,4902007 12,751 9,986 7,518 12,593 13,721 31,167 19,129 18,158 16,191 16,192
Mean 10,189 8,222 6,862 11,828 11,292 22,763 17,791 12,912 10,575 13,550
Standard Deviation
1,870 846 1,172 2,541 2,885 3,925 2,770 3,047 2,784 2,792
Source: Authors’ calculations.
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Appendix Table 4. Growth in Sophistication of Service Exports, by Category, at Global Level (percent)
Transportation Travel Communication Construction Insurance Financial Computer & Information
Royalties & License Fees
Other Business Services
Personal, Cultural & Recreational
ServicesAverage Annual
Growth 1991–2000
4.4 1.9 4.4 -2.3 6.9 5.7 6.9 5.8 4.7 5.8
Average Annual Growth 2000–07
2.5 2.7 2.3 7.0 0.6 6.5 3.9 7.2 5.8 3.4
Source: Authors’ calculations.
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Turning to the goods and services EXPY’s, not just their mean but also their standard deviation has increased over the years, that is, countries are becoming increasingly diverse in their sophistication (Appendix Table 3). This suggests that the potential EXPY has increased, and some countries have started to benefit from this higher potential.
Appendix Table 5. Summary Statistics, Goods and Services EXPY (2007)
GOODS EXPY SERVICE EXPY
Year Mean Standard Deviation Year Mean Standard Deviation
1980 9,706 4,592 1990 6,615 1,258
1990 10,768 4,783 1995 7,900 1,598
2000 12,182 4,586 2000 9,253 1,807
2007 12,509 4,645 2005 10,924 2,179
2009 12,714 4,848 2007 11,859 2,599
Also, countries with more sophisticated exports of either goods or services generally enjoy a higher GDP per capita (Appendix Figure 1).
43
Appendix Figure 1. Sophistication of Exports of Goods, Manufactures and Services versus GDP per capita, 1992 and 2007
7.5
88.
59
9.5
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oods
Exp
ort S
ophi
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atio
n 19
92
6 7 8 9 10log Goods Export Sophistication 1992
88.
59
9.5
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oods
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ort s
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atio
n 20
07
6 7 8 9 10 11log GDP per capita 2007
88.
59
9.5
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anuf
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ring
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rt so
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ticat
ion
1992
6 7 8 9 10log GDP per capita 1992
88.
59
9.5
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anuf
actu
ring
expo
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ion
2007
6 7 8 9 10 11log GDP per capita 2007
7.5
88.
59
9.5
log
Ser
vice
Exp
ort S
ophi
stic
atio
n 19
92
6 7 8 9 10log GDP per capita 1992
88.
59
9.5
10lo
g se
rvic
e ex
port
soph
istic
atio
n 20
07
6 7 8 9 10 11log GDP per capita 2007
Source: Authors’ calculations.Notes: Green denotes Latin America and the Caribbean, black denotes Advanced Economies, red denotes South Asia, blue triangles denote SSA, and navy blue diamonds denote East Asia and the Pacific.
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C. Outlier Regressions
Appendix Table 6 presents outlier regressions. The dependent variable is the sophistication of exports of goods and of services. We control for: log income per capita; log income per capita squared; and size, as proxied by log population. Lastly, we add regional dummies of interest.
We note that China and India are both positive, and typically statistically significant, outliers. In particular, India is a large positive, significant outlier in the sophistication of services. SSA’s sophistication was roughly as expected, given its stage of development and size.
45
Appendix Table 6. Export Sophistication: Outlier Regressions
(1) (2) (3) (4) (5) (6) (7) (8) (9)Goods Export Sophistication Manufacturing Export Sophistication Service Export Sophistication
1991 2000 2006 1991 2000 2006 1991 2000 2006
log GDP per capita) 0.592 0.424 0.705** -0.730 -0.286 -0.193 0.257 -0.182 -0.168(0.671) (0.454) (0.336) (0.518) (0.316) (0.325) (0.247) (0.244) (0.235)
(log GDP per capita)2 -0.0148 -0.00917 -0.0232 0.0527* 0.0282 0.0224 -0.0109 0.0155 0.0159(0.0381) (0.0255) (0.0184) (0.0289) (0.0177) (0.0179) (0.0141) (0.0139) (0.0132)
Geographical Size 0.0678*** 0.0408*** 0.0521*** 0.00493 0.0145 0.00450 0.0179** 0.000860 0.00146(0.0135) (0.0126) (0.00913) (0.0129) (0.0119) (0.0111) (0.00724) (0.00995) (0.00806)
India 0.236** 0.108 0.154** 0.0479 0.0597 0.186** 0.0911** 0.400*** 0.457***(0.0931) (0.0655) (0.0619) (0.113) (0.0752) (0.0759) (0.0390) (0.0671) (0.0516)
China -0.00385 -0.0320 -0.157 0.167 0.105 0.252* -0.0445 0.0645 0.152(0.160) (0.156) (0.121) (0.171) (0.152) (0.146) (0.0813) (0.129) (0.103)
SSA -0.0618 -0.116* -0.00775 0.0108 -0.0352 -0.00707 -0.0660 0.00821 0.0461(0.0958) (0.0676) (0.0715) (0.116) (0.0787) (0.0821) (0.0413) (0.0605) (0.0501)
Constant 4.646 6.031*** 4.507*** 11.58*** 9.540*** 9.271*** 7.308*** 9.508*** 9.553***(2.958) (2.061) (1.532) (2.343) (1.433) (1.484) (1.091) (1.097) (1.067)
Observations 103 125 122 103 125 122 114 124 118R-squared 0.710 0.698 0.752 0.363 0.552 0.576 0.372 0.311 0.509
Notes: These regressions indicate where different regions and countries lie in terms of export sophistication, compared to the global norm, after controlling for the stage of development, size, and other independent variables. *, **, and *** denote significance at the, respectively, 10 percent, 5 percent, and 1 percent level. Robust standard errors are in parentheses.
46
VII. REFERENCES
Barro, Robert, and Jong-Wha Lee, 2010, “A New Data Set of Educational Attainment in the
World, 1950–2010,” NBER Working Paper No 15902.
Dreher, Axel, 2006, “Does Globalization Affect Growth? Evidence from a New Index of
Globalization,” Applied Economics 38 (10): 1091–1110.
Escaith, Hubert, 2008, “Measuring Trade in Value Added in the New Industrial Economy:
Statistical Implications,” MPRA Paper 14454, University Library of Munich, Germany.
Francois, Joseph, and Bernard Hoekman, 2010, “Services Trade and Policy,” Journal of
Economic Literature 48(3): 642–92, September.
Ghani, Ejaz, and Homi Kharas, 2010, “The Service Revolution in South Asia: An Overview,” in:
Ghani, Ejaz, ed., The Service Revolution in South Asia (Oxford University Press).
Gwartney, James, Joshua Hall, and Robert Lawson, 2010, Economic Freedom of the World:
2010 Annual Report (Vancouver, BC: The Fraser Institute).
Hausmann, Ricardo, Jason Hwang, and Dani Rodrik, 2007, “What You Export Matters,” Journal
of Economic Growth 12(1): 1–25.
Johnson, Simon, Jonathan Ostry, and Arvind Subramanian, 2010, “Prospects for Sustained
Growth in Africa: Benchmarking the Constraints,” IMF Staff Papers 57: 119–171.
Lall, Sanjaya, 2000, “The Technological Structure and Performance of Developing Country
Manufactured Exports, 1985–98,” Oxford Development Studies 28(3).
Lall, Sanjaya, John Weiss, and Jinkang Zhang, 2005, “The ‘Sophistication’ of Exports: A New
Measure of Product Characteristics,” Queen Elizabeth House Working Paper No 123,
Oxford University.
Mishra, Saurabh, Susanna Lundstrom, and Rahul Anand, 2011, “Service Export Sophistication
and Economic Growth,” World Bank Working Paper No 5606.
47
Triplett, Jack, and Barry Bosworth, 2004, Productivity in the U.S. Services Sector: New Sources
of Economic Growth (Washington, D.C: Brookings Institution).
World Bank, 2010, World Development Indicators (Washington, D.C.: World Bank).
World Trade Organization, 2009, International Trade Statistics 2009 (Geneva: World Trade
Organization).
